Utilizing XMG-Based Synthesis to Preserve Self-Duality for RFET-Based Circuits

Abstract

Individual transistors based on emerging reconfigurable nanotechnologies exhibit electrical conduction for both types of charge carriers. These transistors [referred to as reconfigurable field-effect transistors (RFETs)] enable dynamic reconfiguration to demonstrate either a p- or an n-type functionality. This duality of functionality at the transistor level is efficiently abstracted as a self-dual Boolean logic, that can be physically realized with fewer RFET transistors compared to the contemporary CMOS technology. Consequently, to achieve better area reduction for RFET-based circuits, the self-duality of a given circuit should be preserved during logic optimization and technology mapping. In this article, we specifically aim to preserve self-duality by using Xor-majority graphs (XMGs) as the logic representation during logic synthesis and technology mapping. We propose a synthesis flow that uses new restructuring techniques, called rewriting and resubstitution for XMGs to preserve self-duality during technology-independent logic synthesis. For technology mapping, we use a novel open-source and a logic-representation agnostic mapping tool. Using the above-proposed XMG-based flow, we demonstrate its benefits by comparing post-mapping areas for synthetic and cryptographic benchmarks with three different synthesis flows: 1) AIG-based optimization and AIG-based mapping; 2) XMG-based optimization with AIG-based mapping; and 3) AIG-based optimization with logic-representation agnostic mapping. Our experiments show that the proposed XMG-based flow efficiently preserves self-duality and achieves the best area results for RFET-based circuits (up to 12.36% area reduction) with respect to the baseline.